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rFIA  

Estimation of Forest Variables using the FIA Database
View on CRAN: Click here


Download and install rFIA package within the R console
Install from CRAN:
install.packages("rFIA")

Install from Github:
library("remotes")
install_github("cran/rFIA")

Install by package version:
library("remotes")
install_version("rFIA", "1.1.2")



Attach the package and use:
library("rFIA")
Maintained by
Hunter Stanke
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-28
Latest Update: 2025-03-10
Description:
The goal of rFIA is to increase the accessibility and use of the United States Forest Services USFS Forest Inventory and Analysis FIA Database by providing a user-friendly open source toolkit to easily query and analyze FIA Data. Designed to accommodate a wide range of potential user objectives rFIA simplifies the estimation of forest variables from the FIA Database and allows all R users experts and newcomers alike to unlock the flexibility inherent to the Enhanced FIA design. Specifically rFIA improves accessibility to the spatial-temporal estimation capacity of the FIA Database by producing space-time indexed summaries of forest variables within user-defined population boundaries. Direct integration with other popular R packages e.g. dplyr tidyr and sf facilitates efficient space-time query and data summary and supports common data representations and API design. The package implements design-based estimation procedures outlined by Bechtold Patterson 2005 doi10.2737SRS-GTR-80 and has been validated against estimates and sampling errors produced by FIA EVALIDator. Current development is focused on the implementation of spatially-enabled model-assisted estimators to improve population change and ratio estimates.
How to cite:
Hunter Stanke (2019). rFIA: Estimation of Forest Variables using the FIA Database. R package version 1.1.2, https://cran.r-project.org/web/packages/rFIA. Accessed 04 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:47), 0.1.0 (2019-10-28 14:30), 0.1.1 (2019-11-12 18:30), 0.2.0 (2020-01-09 18:50), 0.2.1 (2020-04-03 21:20), 0.2.2 (2020-04-27 16:00), 0.2.3 (2020-05-17 00:30), 0.2.4 (2020-09-17 21:00), 0.3.0 (2020-12-07 18:30), 0.3.1 (2021-01-15 06:30), 0.3.2 (2021-06-10 17:20), 1.0.0 (2021-12-15 19:10), 1.1.1 (2025-03-10 16:20), 1.1.2 (2025-09-29 13:20), 1.1.3 (2026-04-30 22:40)
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